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Ashwagandha Promises Calm. The Science Is More Complicated
The popular supplement may help ease stress, but evidence for anxiety remains uncertain–and rare side effects complicate its soothing reputation.
Global survey links financial hardship to lower trust in science
Poor access to health care, limited local influence over research priorities and an unequal distribution of scientific benefits are undermining public confidence in science, experts warn, following the ...
Sam's Club Will Offer 10% Off Disney Gift Cards for Limited Time, Likely to Sell Out Quickly
Ahead of Black Friday, Sam's Club will offer their biannual 10% discount off Disney Gift Cards.
Matthew Golden limited Thursday
Green Bay Packers WR Matthew Golden dealing with shoulder injury
Stony Brook Researchers David Miloschewsky and Supartha Podder Resolve a Decades-Old Puzzle About the Limits of Quantum Computing
Finding a path through a maze is hard, even for quantum algorithms. A quantum computer can find the exit of a certain kind of maze far faster than a classical computer. But can it also give you directions? David Miloschewsky and Supartha Podder of Stony Brook University’s Department of Computer Science have proven that finding
Experts say your health insurance should cover gym memberships to prevent cancer from coming back. Why don't they?
Fitness programs are increasingly viewed as good cancer fighters, but insurers limit the coverage.
The Leap Second Is No More
The metric might not mean much to laypeople, but leap seconds have been a source of contention in the timekeeping community for years. Now, they’re dead.
How healthy are your feet?
Many of us take our feet for granted — until they hurt! In Good Shape finds out how to keep our feet healthy and strong, and what happens when they're pushed to the limit on a 100-kilometer hike.
QED Science adds preprint scoring to research discovery | ETIH EdTech News
QED Science has introduced Insights Feed, combining personalized research recommendations across 250 life science subfields with quality scores for selected preprints. ETIH’s edtech news coverage examines the tool’s features, use of unpublished work and limits of the launch claims.
U.S. taking Putin’s side would be a ‘historic mistake,’ says Zelenskyy
The Ukrainian leader told NBC News’ “Meet the Press” that Ukrainian officials believe the decision to limit Starlink, imposed by Elon Musk’s SpaceX, came from the U.S. government.
Melco Resorts & Entertainment Limited Stock 12‑Month Price Target Cut to $6.14, Implies 48% Upside
Explore more price target data and ratings for Melco Resorts & Entertainment Limited on the Forecasts tab, and track all previous and future analyst recommendations for Melco Resorts & Entertainment Limited in the dedicated News Flow.Select reference data provided by FactSet. Copyright © 2026 FactS…
Sasin and Thai Airways Partner to Bridge Business Education and Real-World Experience
Sasin School of Management, Chulalongkorn University, and Thai Airways International Public Company Limited have signed a Memorandum of Understanding (MOU) to promote cooperation in education and student development, connecting classroom knowledge with practical experience in the business sector.
Families are no longer off-limits in political attacks
Some of the most audacious familial attacks have come from Republicans in tough 2026 races.
Calinos Entertainment Celebrates New Season with 21 New Series
The new slate includes the dramas Love in the Ashes and Salted Love; the limited series Between the World and Us, Runaway, and The Choice; daily drama
Xbox reveals pricing for cloud gaming limits, starting at $3.99 for 10 hours
Cloud playtime packs provide ad-free cloud gaming, including shorter wait times and high-quality streaming
Another limited practice for Adonai Mitchell
Jets WR Adonai Mitchell may be back in lineup after back-to-back limited practices
Six years of SQMS: asking what limits quantum systems and building the answers
The founding director provides perspective on the first six years of a DOE National Quantum Information Science Research Center — the Superconducting Quantum Materials and Systems Center, led by Fermi National Accelerator Laboratory.
Amazon's $220 billion AI bet tests the limits of its empire
Amazon's $220 billion AI buildout is draining cash as power shortages, costly Nvidia servers, and construction challenges pile up.
Thousands rally with Bernie Sanders and Angie Nixon in rainy Ybor City
Their message was helping the working class deal with rising inflation, a lack of health care and unlimited campaign financing by "the oligarchy."
Almost iconic? Political violence and the making of symbolic figures in Brazil’s 2018 elections by Katherine Jensen
Ethnic and Racial Studies ABSTRACT Confederate memorialization is not limited to the United States. After the Civil War, thousands of former Confederates emigrated to Brazil where slavery continued. Santa Bárbara d’Oeste and Americana, in São Paulo State, long celebrated this Confederate heritage. Local memory politics, however, have become unsettled. This article examines local Black movement …
Melco Resorts & Entertainment (NASDAQ:MLCO) Reaches New 52-Week Low
Melco Resorts & Entertainment (NASDAQ:MLCO) Sets New 52-Week Low - Here's What Happened
Bucs’ Josiah Trotter questionable for Steelers game with knee injury
Bucs rookie linebacker Josiah Trotter was limited in practice Friday with a knee injury and is listed as questionable for Sunday’s game against the Steelers. Trotter ranks first on the club in tackles (41) and passer rating allowed (66.
Jaylen Waddle limited Thursday
Chest injury limits Denver Broncos WR Jaylen Waddle Thursday
Ravens upgrade Vega Ioane, Rashod Bateman on Thursday injury report
The Ravens reported several positive updates on their Thursday injury report, but Lamar Jackson remains limited.
Women who changed science missing from GCSE and A-level courses
Despite social, economic and institutional barriers limiting women’s formal participation in science, they made numerous key breakthroughs.
Amazon renames Kindle Unlimited to Kindle Plus and expands access to audiobooks
Kindle Unlimited is now Kindle Plus.
Sundar Pichai: Google’s Frontier Imperative, Compute Scarcity Dilemmas, Future AI Products and Businesses
Alphabet CEO Sundar Pichai has little patience for doubts about Google’s willingness or capacity to compete at the frontier of AI. His company’s latest Gemini 4 Argon model — long-promised and recently delivered — beats OpenAI and Anthropic’s latest public models on coding, math, science, and knowledge-work benchmarks and has placed Google’s AI back among the world’s best. Amid chatter that Google was fine with good-enough lightweight ‘Flash’ models, Pichai pushed back hard against any suggestion that company is limiting its research ambitions. “We won’t do it any other way,” he told me in a Big Technology Podcast interview recorded this week at Google’s Mountain View headquarters. Pursuing cutting-edge research is costly for Google, requiring compute and chips that otherwise could be sold at a high markup by its cloud business. But Pichai said allocating resources to frontier AI development is “ground zero” for Google. “Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development,” Pichai told me. In our conversation, we discussed Argon (which Pichai says processed three times as many tokens as Gemini 3 in the 72 hours after launch), AI’s role in developing better models, the AI interface of the future, competition with OpenAI, Google’s partnerships with Anthropic and Apple, data centers in space, and the nature of his optimism. You can read the full conversation, lightly edited for length and clarity, below, or listen to it on Apple Podcasts, Spotify, YouTube, or your podcast app of choice. Alex Kantrowitz: Google is back at the frontier with Gemini 4 Argon, which beats OpenAI’s and Anthropic’s public models on benchmarks spanning coding, math, science, and knowledge work. The conventional wisdom was that Google had given up on the frontier to focus on fast, good-enough models for its products. That was wrong? Sundar Pichai: Very wrong. Look, we are so committed to being at the frontier. It’s in our DNA. We won’t do it any other way. We’ve been thinking about the AI frontier for well over a decade now. The frontier is very dynamic. It’s very competitive. It’s very exciting. I couldn’t be more pleased with how Argon has come together. We took our time with it. We made sure we tested it safely and deployed it carefully. We took a bit longer than our other models, given its capabilities. Across the board, be it for agentic work, knowledge work, coding, creative tasks, Argon is one of the really good frontier models. The first 72 hours since we launched, it’s almost up to 25 trillion tokens used, which is about three times what Gemini 3.0 had in the first 72 hours. And we are capacity constrained as we are serving it. Excited, but there are always areas….. You know, the frontier is very dynamic, and you have to keep evolving the models. There are areas which we can see we need to improve as well. We’ll be at work on all of that as well. Which areas? On any given model, Argon would be across the board better at everything if you just look even two months back. But the space is so evolving. Even on coding, for example, there are pockets where we know we need to do better, and there’s clear feedback. We’ll make it better. The argument for standard models is that they’re already good enough to build great products, with the frontier valuable only for certain tasks. Meta built Muse with good models rather than the best, and Google could put standard models into Maps, Gmail, and Search. Why isn’t that sufficient? It’s definitely not how I have thought about it at all. We are deeply committed to driving the state of the art and actually pushing where this technology can go, all the way from transformers. That’s a journey we’ve been on. You will see us continue to do that. When you’re at the frontier, you get an earlier look into the emerging capabilities, earlier than others, which helps you better prepare for the future. We are fortunate to have a wide set of opportunities across consumer and enterprise. Some of our cloud customers, for sure, want the model at the frontier. The frontier models will be better at developing the next set of models in an era of recursive self-improvement. I would argue it matters there. Internally, we have definitely seen a steep point of inflection by deploying Argon to our developers. It definitely tackles problems which our previous models could not do. Being at the frontier puts you at the innovation frontier and helps you drive that as well. There is room for models of all sizes and capabilities. That’s why we did Flash, Flash-Lite, etc. I agree with you that you can develop very good product experiences with not necessarily the most frontier model, because they tend to be slower and more expensive too. But we care about the Pareto frontier, and we’re committed to doing all of that. You said developing frontier models gives you a look at what’s coming. What do you see on the horizon? What makes this moment so exciting is you build something which you think is a culmination of months of work, and you put it out. You already see clear headroom ahead. We’ve all been working on these agentic, long-horizon capabilities, but clearly the frontier is going to have multiple of these agents working together to do things. That’s an example of an exciting paradigm underway. It’s also clear to me that users, both in consumer and enterprise, will have access to some multi-agent framework for them, working all the time doing things. It feels like a moment of infinite possibilities. Sergey Brin said one of Argon’s core innovations was relying more on the model to help develop the model. Yet incidents involving OpenAI’s bots breaking containment and Google’s bots accessing a site they shouldn’t have suggest these systems still aren’t perfectly aligned. Isn’t there reasonable cause for concern about accelerating toward recursive self-improvement? There are three parts to your question. Let’s first talk about RSI itself. You’re right, Sergey mentioned RSI being a critical contributor as we are developing Argon. But to be very clear, today, in a continuum, we are pretty far from the end state of RSI or something like that. The right way to describe it is you have RSI loops along with AI researchers in various aspects of model development. You almost have agents helping AI researchers in some automated way work together to build these models. It’s good to at least understand where we are today, and it’s super exciting. I expect that continuum to keep making progress as we go into next year. The second question is around safety. Security comes from defense in depth. You’re talking about alignment, obviously. We all are doing a lot of work to make sure the models are as aligned as possible. But it’s an active area of research, and there are clear gaps. That’s not the only thing we rely on. You have the work you do on alignment, but beyond that, we put a lot of effort into real-time monitoring as these models are working. Making sure you have good telemetry into what’s happening so that you can intervene in real time if you see unexpected behaviors. How you do that, the architecture with which you do that, how you make sure it’s all sandboxed and isolated in a way that it can continue doing its job during real-time monitoring — these are all areas of investment. Obviously, when we deploy these models, giving customers, enterprises, control, both with real-time monitoring, but their ability to decide where they deploy, what type of data which models ever have access to, etc. All that work is very, very important, and we are doing a lot of that. As an industry, we need to constantly up our game and take the time to do all this stuff, including dedicating the compute required to make sure you can safely deploy these models. The third part is: Is it all enough? This is why there are a lot of conversations in the industry, and I think it’s reasonable to be worried. The right way to approach something you worry about is early on thinking about what more we can do. As an industry, you’re definitely seeing increased levels of work on alignment, testing for safety, etc., as we deploy these models. The next step would be developing better standards so there are cross-industry standards of how we do these things, including the ability to evaluate using independent evaluators. If you look at areas like financial controls, we have accounting standards, we have independent auditors. Those are all the next natural steps for us as an industry to work toward, and regulation will end up playing a role as we go through all of that as well. Google pursues both language models and world models, while some other AI companies like OpenAI have focused more heavily on LLMs as the path to AGI. Why is world-model research important to you? As humans, you obviously perceive the world around you, and you’re taking all those inputs. Making sure these models are able to understand the laws of physics, simulate the world in high fidelity. All that, I think, are key enabling blocks for intelligence. We are working across all possible applications of this. Take an area like robotics. It’s not an accident: If you look at embodied reasoning benchmarks, Argon is state of the art. That all comes from our experience building world models. Inherently, I would expect there will be architectures which will converge all of this in the future. But for us, we view this as, today, this jagged frontier that is intelligence. We want to be at the frontier of all the possible approaches, and that will help us both drive better research, better insights, and develop a much better AGI model, is how we think about it. Some people argue Google should focus on selling its computing resources rather than using them for AI research. Cloud wants to sell compute at a high markup, while researchers need a very big computer to build the best models. How do you balance those demands? Ground zero for us is making sure we are investing in the compute that’s needed to be at the AI frontier. In 2015, I set the company to be AI-first. AI is that key horizontal ingredient across everything we do, all the way from Search to Cloud to Waymo. That is ground zero for us, making sure both for research and developing the models that we have enough compute needed. Beyond that, we have these independent businesses which each have their own long-range plans. They’re using those long-range plans to project forward, and we plan for compute for all of them. The cloud team, they have a business and they have a projection and they have demand signals. They have committed contracts. With that help, we can plan on a long-term compute trajectory for them. We’re fortunate to have this wide set of opportunities. There’s no company in the world which isn’t making trade-offs at any given moment in time. But the first principles we operate on is making sure we have enough compute to invest in the frontier, and that’s non-negotiable, and everything else works on top. Remember, we are building our own compute, our own data centers. There are long lead times. The compute we have today is a function of decisions I made in 2024. Even if you think back to a year from today, last year the agentic coding takeoff hadn’t happened. Today, obviously, when you sit and look at anything, everyone is short—not just us, other companies—and everyone wishes you had two times what you had planned for. That comes with the territory. At any given moment in time, we are planning for what we would need two to three years out in the future. You’re going to find some decisions you make may look suboptimal two years out, depending on where the state of the art is. I don’t spend too much time thinking about it. The way I think about compute allocation is making sure Google DeepMind, both for research and frontier model development, is cutting edge in terms of compute access. After that, we plan for all our businesses. It’s great we can provide our compute to other people too, like we have done. It allows us to scale that up, get real tests for it in the widest application set possible, test it in the real world, and make sure we are at the cutting edge of technology at every layer of our AI stack as well. Ben Horowitz relayed on a podcast that Andy Jassy had said compute was sold out until 2028. Are you seeing the same thing? If today a customer is coming out and asking us for compute in ’27, that is incredibly difficult to do. Even last year we went out and leased some short-term compute to accommodate some customers and help them out. But yes, we are all dealing with similar timelines. Every major technology shift seems to involve overbuilding, from railroads to fiber. Do you think that’s happening here? It depends on the time frames you’re looking at. This level of build, if I take a long enough time frame, it makes complete sense to me. We are at early stages of the most consequential technology ever, and this is not like fiber. It’s not dark. We are using it. We are capacity constrained on a daily basis. The applications, the underlying technology is improving rapidly. But running a company, the way I work through the moment is you look at your demand signals. You look at your committed revenue opportunities that you’re getting in the form of contracts. You balance that with the underlying technical capability, or internally you balance how we are using it internally, the model trajectories. Based on all that, you take a disciplined approach—a confident, aggressive, but disciplined approach—to plan out compute. But when you talk about the broader economy as a whole, you’re having people operate with various levels of risk. I focus on what I can control as a company and plan through it. If your question is, can there be an overbuild? Yes, because you can have some constrained components. Remember, what matters is a set of everything you need to build out that compute. Memory, electricity, electricians…. Land. Like 2,000 components or more. You could get constrained at some point. There could be things which cause bottlenecks, and then you could have overbuilds. There could be external shocks to the economy. There are macro risks. All that is possible at any given time. But am I confident that the compute we are planning for, we will have uses for it given enough time? Absolutely, yes. I was in the room when you said AI would be as profound as fire and electricity. If you believe that, shouldn’t you give researchers the biggest possible computer, even at the expense of today’s cloud profits? We’re all doing some form of that. Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development. What you’re seeing is true already. But you want to be thoughtful. Even our AI researchers have some constraints, which are also good. That’s what inspires creativity. That’s what helps you come up with a more efficient algorithmic breakthrough, maybe to use less memory. What we are committed to is to invest what’s needed to stay at the frontier. OpenAI President Greg Brockman told me a few months ago that the ideal AI product might have no interface at all—just as natural as conversation. What do you think the interface looks like in the age of AI? Computing historically has been humans adapting to computing. With AI, it’ll be the other way around. The technology will adapt seamlessly to how humans live and go about their day-to-day life. You want to be able to speak to that AI when you want to. It has context. It can be persistently running somewhere, give you continuity. You’re not dealing with a lot of complexity. It’s natural. All that makes sense to me. That doesn’t mean it won’t have any interface, however. Nowadays, even on my phone, Gemini voice models are so good. I can just press the microphone button. I can just ramble. That’s why we call it Rambler. I can ramble. It intelligently corrects with my personal context. Even my friends’ names, weird names, it gets it right, even if it first guesses it wrong. It’s amazing. I’m not going in, backspacing, editing once I finish saying it. It’s remarkable how good it’s gotten. But there are going to be moments you will need an interface. You may want to entertain yourself. You may want to watch a video. You may ask your AI to create something, and you want to watch it, consume it. The way I think about it is, you want it to be as seamless and as natural as possible, and that you are not doing the hard work adapting to whatever the interface is. The technology is adapting to how you’re working at any given moment in time. When I asked Sam Altman about competition from Google, he argued that OpenAI was building AI-native products and implied Google was bolting AI onto existing ones. Do you accept that framing, and can a “bolt-on” compete with an AI-native product? First of all, it’s a very dynamic moment. We are all pushing each other. OpenAI has pushed us as a company too. This is not just we are doing something to them. Far from it. Yes, Google went into its own version of a code red too. In the AI moment, all of us have to respond with varying levels of urgency at any given moment in time. We are constantly building new products as well. Gemini was built from the ground up as a product—the Gemini app I’m talking about. Or tomorrow, as all of us are adapting to agents, are you bolting agents onto ChatGPT, or are they building it natively? How would you think about that? You can always put these questions back. I don’t think of it that way. I think of it as you want to build world-class product experiences that are AI-native and they are winning. Some of it is adapting products, some of it is rethinking new experiences. They will all be part of how you approach this moment. How do you expect to make money from these AI interfaces? If an agent recommends a product and I buy it, should it take a cut of the sale, even if that’s disclosed? I’m going to put enterprise aside. Consumers are going to increasingly value this technology. Take software developers today. Developers are willing to pay for these coding models because it really helps make them more productive. Nobody would want to code the way they were coding three years ago, or even the same time last year. When you’re delivering value, there’s value to be had. I’ve never seen examples where consumer products really scale to billions of users, where people are using it intensely, and haven’t had monetization to go along with it. If you’re providing value to people, there is inherent value to be had. The nature of it may change. You’re asking a scenario in which agents are doing stuff for you. At the end of the day, you will have commercial needs. The agents need to fulfill those commercial needs. The providers on the other side are going to see value in that. There’s going to be some mechanism by which it gets fleshed out. That’s what an efficient system does. But what matters is that you’re building those world-class consumer experiences. I promised myself one product feature request: Can you make Gemini-powered search in Gmail as good as searching Gmail through ChatGPT? What’s going on here? One of the exciting things we announced recently is the unified Gemini agent for enterprise, and we’re bringing that to consumers. These are persistent agents which run 24/7 in the cloud. We’re spinning up a micro VM effectively for every query, and from the runtime, the harness, the model—it’s all a headless service. It’ll work everywhere, and it has your context with you. You can address this agent whether you’re in Workspace, in Search, in Gemini. Agents are going to drive this unification from a customer experience, which people are looking for. When you have a broad product portfolio and you’re moving forward fast, there are always areas where you’re moving forward faster than some other areas. That’s valid feedback. But we are putting a lot of time and effort into making sure, as we build out our agentic experience, that unification and that capability works well across all these services. People have asked where Google’s equivalent of Muse or Dots is. Do you anticipate creating a new product to compete with them? Our goal with Gemini is to be a personal, proactive, and powerful assistant. That’s what we are working toward. You saw us describe the early versions of it at Google I/O this year with Spark. Effectively, already, if you open the Gemini app as a Pro or an Ultra user, you see Chat and Task, and they start giving you that agentic experience. With Argon now, that capability is dramatically accelerated. What we announced recently in our enterprise event, we are bringing that to consumers as well. Soon in Gemini, you will be able to ask something, and it’s a continuum. You don’t need to think about whether you’re asking a chat or an agentic task. It’ll just automatically do the right thing, and it can work persistently in the background securely and get things done for you. Already, empirically, when I look at what’s coming into Gemini in our app, last year you would have tagged them and most of them would have been chats. But a steadily growing percentage is already agentic tasks in Gemini. Yes, we are going to bring personal agents to our consumers. It’ll work in the Gemini app. It’ll work in Google Search. It’ll work in Gmail. You can address it, call it, etc. We want to make sure we’re getting it right. It’ll be powered by Argon, and we are very excited to bring it to our users. Google has invested and committed tens of billions of dollars to Anthropic. What do you see in Dario Amodei that makes you want such a deep investment and partnership? Very early on, when we looked at the founding team of Anthropic, it was very clear to us this was a world-class team which was involved in some of the earliest GPT models. We were quickly able to assess that they would be at the frontier. We’ve always tried to identify and partner with companies which would be at the cutting edge of technology. We’ve done that with SpaceX. We’ve done that with Anthropic. That’s what we saw, and we had a chance to partner. Is your partnership with Apple to license Gemini for Siri expanding, contracting, or standing still? For both us and Apple, that partnership was about translating the capabilities of AI into better experiences for users. I thought Apple has done a phenomenal job of incorporating—they customize these models and build it into Siri—and it’s been great to see the reception. We are committed to doing more. You’re going to do more with them? There’s nothing specific to comment, but it’s a partnership. It’s working well. What have you learned so far about the feasibility of data centers in space? It’s a very exciting project. Projects like this remind me—I still recall that moment in the desert for the DARPA Grand Challenge, watching the Stanley car compete in it, which ended up being the basis for Waymo. With all these technologies, you’re at a moment in time where it looks a bit like sci-fi, but 10 to 20 years down the line, it’s actually working in a meaningful way. I feel the same in space. We’ve always believed in betting big on these technologies. Quantum has been a great example of it. We’re probably 10 years into the journey. Waymo, we are almost 20 years into the journey. Space, we are two to three years into the journey. It’s clear to me that it’s an approach which will make a lot of sense in the future. Being in sub-synchronous orbits with 24/7 access to the most abundant form of energy we have access to will make a lot of sense for this exponential increase in compute that we are going to need. Having said that, this is a challenging project. The team has disciplined milestones. It was a super exciting milestone to send the TPUs up to space. Sometime, as we are speaking, we are expecting a “hello world” moment from them. I look forward to seeing that happen, and we’ll continue investing here too. You previously said 25% of the code written within Google was written by AI. What’s the number today? That number in our world today is meaningless in the sense that every part of what we now touch is influenced by AI deeply. What we are tracking with Argon, for example, it’s been a point of inflection. People are using Argon to really go tackle complex projects, including projects which affect millions of lines of code. In the four weeks since we have launched Argon, we have seen a 30% increase in CLs, and more importantly, almost a similar increase—a one-third decrease in rollbacks. People are writing code more productively and better code with it. We are tracking it with newer metrics now. How are you dealing with opposition to data centers? If you can’t build in the U.S. the way you want to, where else do you go? We’re very committed to building our data centers very responsibly. When I look at our largest data centers in some of the communities where we have been the longest, I visit them, I talk to people. There are people who come and tell us their kids have gone to college because of our investments in these communities, and we’ve grown in those communities. To me, this is about doing it right. Engaging with the communities early, doing it transparently. We are committed to making sure we are bringing incremental power, and we cover 100% of the cost of our power needs for these projects. It’s understanding the impact on neighborhoods and making sure you’re working thoroughly to address them. Done rightly, you can continue making progress. But we are constantly taking feedback into account. I do worry not everyone operates the same way. People have been surprised by data centers showing up in their backyard. Those are all important. As an industry, we should continue to do better. But part of the reason, in a 20-year time frame, we are thinking about things like data centers in space is making sure we are able to put these data centers where maybe the trade-offs will be different. What unproven area of AI is Google working hardest to crack? Is it continual learning—getting models to keep updating after release—or something else? There are multiple parallel paths. You saw with Argon we have a million output tokens. With our Gemini models early on, we had a one-million context window on the input side. These are all examples of breakthroughs we are constantly working on. How do you think about synthetic data? How do you think about continual learning? How do you think about more efficient architectures? We do dedicate a meaningful percentage of our compute to these research bets too. It always goes hand in hand, including our world models. Those are all bets we are placing. Sometimes, as part of these bets, there are ideas that emerge which just make their way into the mainline models. Maybe we don’t fully talk about it, but we have multiple steps in these areas. Working in technology requires optimism that building something will improve the world, but those bets can leave real consequences when they fail. I recently returned to a town in El Salvador where enthusiasm for Bitcoin had given way to unfinished construction and something resembling a ghost town. How do you maintain the optimism you spoke about in your Stanford commencement address while accounting for those risks? I genuinely have a deep conviction that improving technology and improving access to technology makes people’s lives better. It’s been my personal experience in my life, out of which comes that deep conviction, optimism. But with that, I’ve always felt humanity’s journey is always about working hard to harness that technology to make it work well for society. The optimism is not an optimism that you just build whatever you want, whenever. You work hard to make sure you’re building technology in the service of humanity, to make the human condition better. That’s got to be the defining goal as we are approaching it. With that framework, I’m very, very optimistic. We are in very early stages of the kind of progress that we are going to see on many areas. We’re all talking about areas like healthcare. A lot of the progress is ahead. The ability to make things in a fundamentally cheaper way on many things where things have been getting expensive for a long, long time, discovering new materials, etc., which really bend the curve—it’s tough to step today and understand the impact of all that, but they’re going to be very profound. I’m very optimistic, but we have to be rightfully concerned about all the ways this technology can go wrong. Sundar, I know you don’t do many of these. Thank you. Thanks, Alex. Appreciate it.
The Vogue Business Spring/Summer 2027 Size Inclusivity Report
Amid accelerating access to GLP-1s, conservative undercurrents and a few glimmers of hope, curve representation on the runway remains low at just 2.5%.
Arsenal must play to their strengths, not entertain the neutrals
Arsenal’s attacking limitations are clear, but defensive strength can keep their title challenge on course until January. With tough away trips ahead, Arteta should embrace what his team do best while finding ways to turn control into more chances.
Zach Charbonnet logs full practice Wednesday
Seattle Seahawks RB Zach Charbonnet not limited by knee on Wednesday
Judge limits election-related immigration stops amid broader legal war ahead of midterms
An unprecedented election war is playing out between the Trump administration and California in federal court, with a slate of cases proceeding at breakneck speed ahead of the Nov. 3 election.
Turn Calf Health Records Into Herd Improvements
There is a cycle of incomplete calf health records and limited veterinary feedback. Breaking it requires practical recordkeeping systems and a commitment to turning data into management decisions.
Airbnb cracks down on checkout chore lists as hosts face new limits
Airbnb's new checkout rules bar hosts from asking guests to strip beds, wash dishes or do laundry, but some reasonable requests are still allowed.
Michiganders to vote on limiting political donations by utility companies, government contractors
Michigan voters will have a chance to decide whether to limit certain campaign finances through a citizen-led initiative.
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Toppenish School District receives $7.5 million federal grant to expand mental health services for students
The BriefThe Toppenish School District has been awarded up to $7.5 million through Project AWARE (Advancing Wellness and Resiliency in Education), a federal grant administered by the Substance Abuse and Mental Health Services Administration (SAMHSA).The grant will provide up to $1.5 million annually over five years to expand mental health services, strengthen substance use prevention and intervention, and improve access to support for students.District officials say the funding will help address identified gaps in services, particularly drug and alcohol counseling at the high school level, and will allow the district to build capacity for long-term mental health support.TOPPENISH, WASHINGTON — The Toppenish School District has been awarded up to $7.5 million through Project AWARE (Advancing Wellness and Resiliency in Education), a federal grant administered by the Substance Abuse and Mental Health Services Administration (SAMHSA), to expand mental health services and substance use prevention for students.District officials said access to mental health resources has been limited, making it difficult for some students and families to get the support they need. The federal Project AWARE grant will help address those challenges by bringing schools and local healthcare providers together to better support students.The grant will provide up to $1.5 million annually over five years to expand mental health services, strengthen substance use prevention and intervention, and improve access to support for Toppenish students. Deputy Superintendent Dr. Jeff Camero said the district is focused on coordinating with service providers in the area to work as a unified team."We made the awareness with the grant. But looking at all the service providers in the area and how can we all together work as a team?" Camero said.Camero said the district wants to use those resources to reach students earlier and provide more support for those struggling with their mental health. The district plans to address a range of mental health challenges, from anxiety and depression to youth suicide risk. Camero emphasized the importance of supporting students in grades eight through twelve, where suicide rates are a particular concern."Making sure from anxiety to depression, making sure that we can help support our students at those levels, but also the youth suicide risk, looking at that as a top in this area, in our grades, you know, eight, for example, eight through 12, looking at suicide rate and looking at how whether we look at the ACES or whatever program we're looking at, that's federal, how that connects and how we can better serve our students with this extra funding," Camero said.The funding will allow the district to bring in additional staff, including mental health and substance use specialists, to work directly with students and connect families with community resources. The district is already posting positions, including a director role, with additional positions expected to follow.District officials are also thinking beyond the grant's five-year timeline. Brittany Kaple, Director of Public Relations for the Toppenish School District, said the intent is to build capacity and establish connections that will sustain mental health services even after the grant funding ends."We do have the director position already posted, with some of our other positions following really close behind that. But the intent is to, you know, it's a five-year grant, so those positions would be funded for that five years. But there's also the intent to build capacity and make those connections so that at the end of the grant, when that money, you know, if that money is not renewed," Kaple said.As student mental health needs continue to evolve, access to drug and alcohol counseling has become an important priority for the district. Kaple said teachers and staff have been raising concerns about the need for more support, especially at the high school level."And that was something that was also an identified need by our high school staff when the superintendent met with them last school year. They said that that was a really great need, something that they felt was a gap in services that we were providing for our students. And so this is going to be one way to help support that need," Kaple said.The Toppenish School District says its goal is to ensure students and families have access to the support they need, both now and in the years ahead. Additional positions, including drug and alcohol counselors and family engagement specialists, are expected to be posted in the coming weeks. News Sunnyside City Council navigates 2027 budget planning Monique Garcia News "Dancing with the Stars" champion J.R. Martinez shares message of resilience during Central Washington visit Tyler Wargo News Toppenish, Mattawa educators honored at state Educator of the Year Awards Erin Wencl News Kennewick educator named 2027 Washington Teacher of the Year Erin Wencl News Voters to decide the next Yakima County Sheriff Monique Garcia COPYRIGHT 2026 BY APPLE VALLEY NEWS NOW. ALL RIGHTS RESERVED. THIS MATERIAL MAY NOT BE PUBLISHED, BROADCAST, REWRITTEN OR REDISTRIBUTED.
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New Richland Lab Could Transform How Scientists Study Microbes and Boost Regional Jobs
The BriefGroundbreaking held Tuesday: PNNL officially began construction on the M2PC lab, a 30,800-square-foot facility funded by the U.S. Department of Energy's Office of Science that will study soil microbes to improve crop productivity and develop new biotechnology applications. The facility will be open to researchers from around the nation and the world.Research timelines could shrink dramatically: The facility's automation and AI capabilities could reduce experiments that currently take six months to just 72 hours, allowing scientists to explore more possibilities faster than ever before.New jobs coming to the Tri-Cities: The project is expected to create positions for automation engineers, AI experts, roboticists, technicians, and skilled craftspeople, with the facility opening in 2029.RICHLAND, Wash. — Pacific Northwest National Laboratory broke ground Tuesday on a first-of-its-kind facility that could accelerate scientific discoveries about the microscopic organisms living in soil—organisms that may hold the key to growing more food and developing new energy technologies.The Microbial Molecular Phenotyping Capability, or M2PC, represents a significant investment in automation and artificial intelligence to speed up research that traditionally takes years to complete. The 30,800-square-foot facility will house more than 100 connected automated instruments designed to study microbes at a pace and scale never before possible.Reshaping Agriculture's FutureThe M2PC facility will not put a new tool directly into a farmer's hands tomorrow morning, but it is actively reshaping the commercial pipeline to solve agriculture's biggest headache with biologicals: inconsistent field performance. For years, PNNL researchers have explored how microbes work and how they might help produce useful materials, advance energy technologies, and address challenges involving critical materials and minerals. But those experiments have been limited by what researchers could accomplish by hand."They can be used to provide nutrients to a plant so that the plant would grow more. So, like increasing your crop productivity, for example," said Douglas Mans, PNNL's Associate Laboratory Director for Integrated Discovery Sciences.PNNL's own research shows soil microbes can help plants access nutrients and withstand drought—benefits that could prove crucial as farmers face growing environmental pressures. The M2PC facility will allow scientists to identify and optimize useful microbes faster than ever before, accelerating the development of biological solutions that actually work consistently in the field.What Makes M2PC UniqueThe Microbial Molecular Phenotyping Capability differs from traditional research labs because it operates as a first-of-its-kind, AI-enabled autonomous laboratory designed to shrink experimental timelines from years down to months or weeks. The M2PC lab will connect more than 100 automated instruments to grow microbes, prepare samples, measure their behavior, and link observations to the molecular processes behind them. Artificial intelligence will help analyze results and guide the next experiments, allowing scientists to explore more questions faster.Deb Gracio, PNNL Director, emphasized the transformative potential during Tuesday's groundbreaking ceremony: "Research that has taken years will become possible in months and hopefully in weeks."That acceleration is already being demonstrated. PNNL's smaller automated lab, called the Anaerobic Microbial Phenotyping Platform or AMP2, completed three experimental cycles in just 72 hours—a process that normally would have taken about six months."That normally would have taken us about six months … and we were able to do that in 72 hours," Mans said.The AMP2 laboratory is not being closed or replaced. Instead, the current 1,800-square-foot laboratory serves as an active prototype and precursor for the much larger M2PC facility. AMP2 will continue operating as a separate lab designed to run anaerobic experiments—those conducted in the absence of oxygen—while M2PC will focus on aerobic research.Broader Applications Beyond AgricultureWhile improving crop productivity is one important application, the M2PC facility is designed to support research into multiple areas critical to national priorities. The lab will advance research into biofuels, manufacturing materials, and energy technologies. It will also help researchers understand how microbes respond to environmental changes and how to design biological systems for biotechnology applications.As a flagship component of the Department of Energy's Genesis Mission, M2PC represents a significant investment in using artificial intelligence and automation to accelerate U.S. scientific discovery. Dorothy Koch, Associate Director of the DOE Office of Science Biological and Environmental Research program, highlighted the facility's importance during the groundbreaking."M2PC will accelerate biological discovery and design," Koch said, noting that the facility is expected to conduct a minimum of 500 strain experiments per week, 100 microbiome experiments per week, and take a million measurements per month.Economic Opportunity for the RegionBeyond the scientific breakthroughs, the M2PC project represents significant economic opportunity for the Tri-Cities region. The facility will require hiring automation engineers, AI experts, technicians skilled in operating robotics, and specialized craftspeople to build and maintain the sophisticated equipment."We're anticipating that type of hiring," Mans said when asked about job creation.PNNL has already begun recruiting talent nationally and internationally for positions related to the smaller AMP2 lab, bringing automation engineers from cities like Boston and San Francisco to work in the region. The M2PC facility is expected to accelerate that trend."This capability won't really exist anywhere else in the world," Mans said, suggesting the facility could become a draw for scientific talent seeking to work on cutting-edge biotechnology research.Timeline and Next StepsThe M2PC facility is expected to open in 2029. Between now and then, construction crews will level and prepare the ground, while the building takes shape. Simultaneously, Ginkgo Bio Works, the automation contractor, will build the facility's automation components off-site so they can be installed as the building is completed.In the interim, PNNL researchers and the broader scientific community will begin planning the first experiments to be conducted in the facility, ensuring research is lined up and ready to begin as soon as the doors open.The groundbreaking ceremony included representatives from the Department of Energy, PNNL leadership, and elected officials at the federal, state, and local levels, underscoring the project's significance to the region and the nation's biotechnology future. News The U.S. Department of Energy Secretary tours Pacific Northwest National Laboratory Dan Hanson, Apple Valley News Now News Beyond DNA: Scientists Explore New Frontiers in Biology Research Dan Hanson, Apple Valley News Now News TRIDEC optimistic that Hanford, PNNL will see funding in national budget Robert Desaulniers News Big picture science: monitoring the Yakima River Basin News PNNL research could shape the future of fighting fentanyl COPYRIGHT 2026 BY APPLE VALLEY NEWS NOW. ALL RIGHTS RESERVED. THIS MATERIAL MAY NOT BE PUBLISHED, BROADCAST, REWRITTEN OR REDISTRIBUTED.
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Plague is stoppable. The next health threat may not be.
The word plague is scary. Centuries ago, the Black Death killed tens of millions of people and changed the course of history. Plague still kills people around the world, and the word still evokes catastrophe. New fears of plague surfaced on October 2, when a lab worker in Irkutsk, Russia, died of pneumonia. Reports suggested that she may have contracted plague through a laboratory exposure. Understandably, people were alarmed. On October 7, the World Health Organization called for the Russian Federation to be transparent about what it knew. WHO issued an update on October 10. Russian authorities told WHO that testing did not identify plague and that investigations found no laboratory release. WHO said confidence in its risk assessment remained limited and that further clinical, epidemiological, and laboratory information was needed. The cause of the woman’s illness remains unknown, and WHO says a laboratory-associated exposure cannot be excluded. As I explained in a recent interview, this incident is very unlikely to lead to a pandemic. Plague is still active, including in the U.S., which sees a handful of cases each year. But it is a disease we can prevent and treat. Plague doesn’t spread readily, and it responds to antibiotics. The standard response—isolate the patient, trace contacts, and administer antibiotics and monitor for symptoms among contacts for seven days—works. We have even planned for antibiotic-resistant plague. At CDC, we developed a playbook for antibiotic-resistant plague and ran exercises on how to find and stop it. CDC guidance anticipates engineered resistance and recommends two different classes of antibiotics if there’s reason to suspect it. There is no evidence that resistance—or even confirmed plague—is involved in this incident. We have thought through how to address plague, but we’re not ready for the next major health threat that emerges from a lab or from animal spillover to humans. What should concern people is how little stands between the world and the next pathogen to get loose. Since peak COVID, epidemic preparedness has fallen off the political agenda, but the risk is greater than ever. More labs handle dangerous pathogens with more ways to make those pathogens deadlier, and more people live and work in close contact with animals. There are actions we can take now: We need better lab safety in every country. The number of labs that work with dangerous pathogens has increased worldwide over two decades, but there’s no enforceable international standard and no inspection regime; the Biological Weapons Convention, fifty years on, still has no verification mechanism. Labs that study dangerous germs need strong safety systems, training, and oversight. We need to reduce spillover events. Three in four emerging human infections start in animals, and there’s a lot we can do to reduce spillover risk, but the world is doing very little of it. Live-animal markets are one place to act. For instance, closing live-bird markets helped control H7N9 influenza in China. Reducing opportunities for people to encounter infected animals can prevent infections before they become outbreaks. In The Formula for Better Health, which is now out in paperback along with the hardcover, Kindle, and audiobook versions, I argue that labs do too many risky experiments with too many dangerous pathogens in too many institutions, and that every experiment should first answer one basic question: Is the likely benefit greater than the risk? Spillover risk can also be reduced: In the book, I discuss how Brazil cut its deforestation rate by 70% from 2004 to 2012 while increasing agricultural production and reducing risky contact between people and forest animals. We need faster detection and response. Delay costs lives. Strong surveillance, good labs, and trained responders can turn a single case into a small cluster of infections instead of an epidemic. Resolve to Save Lives has worked for nearly a decade to help countries find and stop outbreaks faster. The 7-1-7 target, which Resolve to Save Lives developed with partners in Uganda and elsewhere, provides a clear standard: detect within 7 days, notify within 1 day and complete all essential early response actions within 7 days. In Uganda’s Kasese district, for example, a review of a measles outbreak using 7-1-7 identified shortages of accessible funds, fuel, and vehicles that delayed the response. District leaders established funds they could access quickly. When, a few months later, the Crimean-Congo hemorrhagic fever appeared, the district detected it in three days, notified authorities in one, and mounted an effective response in two. Only one case was confirmed, and the patient survived. Because funds were available before the emergency, authorities were prepared and able to act. This kind of preparation can’t wait until the next crisis begins. Plague is an old disease we that know how to stop. The next threat may be harder to recognize, harder to treat, and easier to spread. Safer labs, less risk of spillover, and faster outbreak detection and response need sustained investment now, while we still have time to prevent the next emergency. Share
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(ANALYSIS) Political shamelessness threatens democracy by weakening leaders’ respect for ethical principles and the rule of law. Drawing on Plato’s Laws, this article explores reverence as a virtue that encourages humility, self-restraint and recognition of human limitations, arguing that responsibl
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